health life sciences medicine
This dataset, named PolySomnoGraphic Inter-scorer Performance Assessment (PSG-IPA) database, comprises 20 polysomnography (PSG) recordings and related multi-expert scoring annotations. It was utilized in a study to evaluate inter-scorer variability, specifically assessing reliability and scoring times associated with various PSG review tasks. The study also aimed to compare the impact of computer-assisted (semi-automatic) scoring versus unassisted visual analysis on these factors. The dataset includes recordings of common raw PSG signal activity, such as electroencephalography (EEG), electrooculography (EOG), electromyography (EMG) of both the chin and lower limbs, electrocardiography (ECG), and various respiratory derivations. Each recording is accompanied by both manual and computer-assisted scorings, performed by 12 independent expert sleep technologists. This comprehensive resource offers significant value for further research into PSG inter-scorer variability, as well as for the development and performance assessment of automated sleep stage and event detection algorithms.
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Creative Commons Attribution 4.0 International Public License
https://doi.org/10.13026/esx0-nw71
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PSG-IPA: A PolySomnoGraphic Inter-scorer Performance Assessment database was accessed on DATE from https://registry.opendata.aws/psg-ipa.
arn:aws:s3:::physionet-open/psg-ipa/us-east-1aws s3 ls --no-sign-request s3://physionet-open/psg-ipa/